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Record W4387380008 · doi:10.1210/jendso/bvad114.1675

SAT370 Economic Burden of Endometrial Cancer Associated with Polycystic Ovary Syndrome

2023· article· en· W4387380008 on OpenAlexaboutno aff
Lauren Pace, Daniela Markovic, Richard P. Buyalos, Fernando Bril, Ricardo Azziz

Bibliographic record

VenueJournal of the Endocrine Society · 2023
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsEndometrial cancerMedicinePolycystic ovaryGynecologyCancerMeta-analysisFamily medicineInternal medicineInsulin resistance

Abstract

fetched live from OpenAlex

Abstract Disclosure: L.A. Pace: None. D. Markovic: None. R.P. Buyalos: Employee; Self; Fertility and Surgical Associates of California. F. Bril: None. R. Azziz: Advisory Board Member; Self; Arora Forge. Consulting Fee; Self; Rani Therapeutics, Spruce Biosciences, Fortress Biotech, Core Access Surgical Technologies. Grant Recipient; Self; Foundation for Research and Education Excellence, Ferring Pharmaceuticals. Stock Owner; Self; Martin Imaging. Background: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among reproductive aged females, affecting approximately 6 million U.S. women. Endometrial cancer, in turn, is the most common gynecological malignancy and the fourth most common cancer overall in female patients. Objectives: To assess the excess economic burden associated with endometrial cancer in women with PCOS. Method: Using PRISMA guidelines for systematic review, we searched PubMed, Web of Science, Scopuse, and Embase for all studies on endometrial cancer in patients with known PCOS. Excluded studies were reviews and case reports, those not conducted in human subjects, without controls, without full text available, or reporting solely on diseases other than PCOS. Selected studies were assessed for quality using the Newcastle-Ottawa Scale. Meta-analysis was performed using the DerSimonian-Laird random effects model to assess the pooled risk ratio (RR) for the association between PCOS and endometrial cancer, then calculation of the excess cost was assessed in U.S. dollars (USD), adjusted for inflation using a medical care inflation calculator. Result: We screened 98 studies by title and abstract, 32 titles in full text, and included 11 articles. Pooled RR was 2.90 (95% CI 1.57-5.37), p=0.0196. In the U.S., overall prevalence of endometrial cancer in patients with PCOS is 0.409%, compared with baseline estimated five-year prevalence (2014-2019) of endometrial cancer in all women of 0.141%, or 235,596 cases. The excess prevalence of endometrial cancer in women with PCOS is therefore 0.2679%, or approximately 361 women. Direct healthcare costs associated with endometrial cancer per patient per year were estimated to be $8,597, when adjusted for inflation to 2022 costs. Therefore, the excess cost of endometrial cancer related to PCOS is estimated at 361 x $8,597 = $3.1 million per year in 2022 USD. Conclusion: In 2022 USD, the excess annual healthcare cost for endometrial cancer care in patients with PCOS exceeds $3 million per year. While the overlap between the risk factors and pathophysiologic underpinnings of both conditions is well-known, PCOS is not always directly addressed as a risk factor for endometrial cancer. Given the findings of this meta-analysis, taken in combination with previously collected data estimating the annual healthcare costs associated with PCOS diagnosis and treatment alone, to exceed $2 billion, we advocate for and increased focus in the global health, policy, and scientific communities to better address this condition and its sequelae. Funding: Foundation for Research and Education Excellence Presentation Date: Saturday, June 17, 2023

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.010
Bibliometrics0.0100.011
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.288
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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